Dose-response relationship between arsenic exposure and the serum enzymes for liver function tests in the individuals exposed to arsenic: a cross sectional study in Bangladesh

<p>Abstract</p> <p>Background</p> <p>Chronic arsenic exposure has been shown to cause liver damage. However, serum hepatic enzyme activity as recognized on liver function tests (LFTs) showing a dose-response relationship with arsenic exposure has not yet been clearly documented. The aim of our study was to investigate the dose-response relationship between arsenic exposure and major serum enzyme marker activity associated with LFTs in the population living in arsenic-endemic areas in Bangladesh.</p> <p>Methods</p> <p>A total of 200 residents living in arsenic-endemic areas in Bangladesh were selected as study subjects. Arsenic concentrations in the drinking water, hair and nails were measured by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The study subjects were stratified into quartile groups as follows, based on concentrations of arsenic in the drinking water, as well as in subjects' hair and nails: lowest, low, medium and high. The serum hepatic enzyme activities of alkaline phosphatase (ALP), aspartate transaminase (AST) and alanine transaminase (ALT) were then assayed.</p> <p>Results</p> <p>Arsenic concentrations in the subjects' hair and nails were positively correlated with arsenic levels in the drinking water. As regards the exposure-response relationship with arsenic in the drinking water, the respective activities of ALP, AST and ALT were found to be significantly increased in the high-exposure groups compared to the lowest-exposure groups before and after adjustments were made for different covariates. With internal exposure markers (arsenic in hair and nails), the ALP, AST and ALT activity profiles assumed a similar shape of dose-response relationship, with very few differences seen in the higher groups compared to the lowest group, most likely due to the temporalities of exposure metrics.</p> <p>Conclusions</p> <p>The present study demonstrated that arsenic concentrations in the drinking water were strongly correlated with arsenic concentrations in the subjects' hair and nails. Further, this study revealed a novel exposure- and dose- response relationship between arsenic exposure metrics and serum hepatic enzyme activity. Elevated serum hepatic enzyme activities in the higher exposure gradients provided new insights into arsenic-induced liver toxicity that might be helpful for the early prognosis of arsenic-induced liver diseases.</p

Algorithms and data structures for cache-efficient computation: theory and experimental evaluation

textThe ideal-cache model is an abstraction of the memory hierarchy in modern computers which facilitates the design of algorithms that can use the caches (i.e., memory levels) in the hierarchy efficiently without using the knowledge of cache parameters. In addition to possibly running faster than traditional flat-memory algorithms due to reduced cache-misses, these cache-oblivious algorithms are also system-independent and thus more portable than cache-aware algorithms. These algorithms are useful both in applications that work on massive datasets and in applications that run on small-memory systems such as handheld devices. The major contribution of this dissertation is a number of new cache-efficient and cache-oblivious algorithms and data structures for problems in three different domains: graph algorithms, problems in the Gaussian Elimination Paradigm (GEP), and problems with dynamic programming algorithms. Among graph problems we concentrate on shortest path computation, and for the computation-intensive problems in the latter two domains we also present efficient parallelizations of our cacheoblivious algorithms for distributed and shared caches. We perform extensive experimental study of most of our algorithms, and compare them with best known existing algorithms and software. In the area of graph algorithms and data structures, we introduce the first efficient cache-oblivious priority queue supporting Decrease-Key operations, and use it to obtain the first non-trivial cache-oblivious single-source shortest path algorithms for both directed and undirected graphs with general non-negative edge-weights. Our experimental results show that shortest path computation using a light-weight version of this new priority queue is faster than using highly optimized traditional priority queues even when the computation is in-core. We also present several new cache-efficient exact and approximate all-pairs shortest path algorithms for both weighted and unweighted undirected graphs. The Gaussian Elimination Paradigm (GEP) includes many important practical problems with constructs similar to that in Gaussian elimination without pivoting, e.g., Floyd-Warshall’s all-pairs shortest path, LU decomposition without pivoting, matrix multiplication, etc. We present a general cache-oblivious framework for cache-efficient sequential and parallel solution of any problem in GEP. Our experimental results comparing our cache-oblivious algorithms with industrial-strength cache-aware BLAS (i.e., Basic Linear Algebra Subprogram) code suggest that our GEP framework offers an attractive trade-off between efficiency and portability. In the domain of dynamic programs, we present efficient cache-oblivious sequential and parallel algorithms for a number of important dynamic programs in bioinformatics including optimal pairwise sequence alignment, median of three sequences, and RNA secondary structure prediction with and without (simple) pseudoknots. All our algorithms improve significantly over the cache complexity of earlier algorithms, and either match or improve over their space complexity. We empirically compare most of our algorithms with the best publicly available code written by others, and our experimental results indicate that our algorithms run faster than these software.Computer Science

Multicore-oblivious Algorithms

Rezaul Alam Chowdhury of Boston University presented a lecture on March 28, 2011 from 10:00 am to 11:00 am in room 1116 of the Klaus Advanced Computing Building on the Georgia Tech campus.Runtime: 51:10 minutes.Multicores represent a paradigm shift in general-purpose computing away from the von Neumann model to a collection of cores on a chip communicating through a cache hierarchy under a shared memory. Designing efficient algorithms for multicores is more challenging than that for traditional serial machines, as one must address both caching issues and shared-memory parallelism. As multicores with a wide range of machine parameters rapidly become the default desktop configuration, the need for efficient, portable code for them is growing. This talk will mainly address the design of efficient algorithms for multicores that are oblivious to machine parameters, and thus are portable across machines with different multicore configurations. We consider HM, a multicore model consisting of a parallel shared-memory machine with hierarchical multi-level caching, and we introduce a multicore-oblivious (MO) approach to algorithms and schedulers for HM. An MO algorithm is specified with no mention of any machine parameters, such as the number of cores, number of cache levels, cache sizes and block lengths. However, it is equipped with a small set of instructions that can be used to provide hints to the run-time scheduler on how to schedule parallel tasks. We present efficient MO algorithms for several fundamental problems including matrix transposition, FFT, sorting, the Gaussian Elimination Paradigm, list ranking, and connected components. The notion of an MO algorithm is complementary to that of a network-oblivious (NO) algorithm, recently introduced by Bilardi et al. for parallel distributed-memory machines where processors communicate point to-point. Indeed several of our MO algorithms translate into efficient NO algorithms, adding to the body of known efficient NO algorithms. Towards the end of this talk I will give a brief overview of some of my recent work related to computational sciences. First I will talk about "Pochoir" (pronounced "PO-shwar") - a stencil computation compiler for multicores developed at MIT CSAIL. Stencils have numerous applications in computational sciences including geophysics, fluid dynamics, finance, and computational biology. Next I will talk about "F2Dock" - a state-of-the-art rigid-body protein-protein docking software developed at UT Austin in collaboration with the SCRIPPS Research Institute. Docking algorithms have important applications in structure-based drug design, and in the study of molecular assemblies and protein-protein interactions

Adsorption dynamics of cobalt [Co (ii)] on rubber granules

The removal kinetics of Co(II) by waste tyre rubber granules was deliberated. Rubber granules (150300 µm) were used as sorbent. At the 4 mg/l and 15 g/l concentrations of Co(II) and adsorbent respectively, 83.2% removal was found in 180 min. Reaction kinetic followed a second order equation that was applied for the analysis of rate constant. At 30°C, rate constant was calculated to be 1.25 × 10−2 min−1. Among different isotherm models, the Freundlich model was found to produce a better regression coefficient. Removal of Co(II) was found to be pH dependent

Cacheoblivious shortest paths in graphs using buffer heap

We present the Buffer Heap (BH), a cache-oblivious priority queue that supports Delete-Min, Delete, and Decrease-Key operations in O ( 1 B log2 N) amortized block transfers from B external memory, where B is the (unknown) block-size and N is the maximum number of elements in the queue. As is common in cache-oblivious algorithms, we assume a ‘tall cache ’ (i.e., M = Ω(B 1+ɛ), where M is the size of the main memory). We also assume the Decrease-Key operation only verifies that the element does not exist in the priority queue with a smaller key value, hence it also supports the insert operation in the same amortized bound. The amortized time bound for each operation is O(log N). We also present a Cache-Oblivious Tournament Tree (COTT), which is simpler than the Buffer Heap, but has weaker bounds. Using the Buffer Heap we present cache-oblivious algorithms for undirected and directed single-source shortest path (SSSP) problems for graphs with non-negative edgeweights. On a graph with V vertices and E edges, our algorithm for the undirected case performs O(V + E B log V 2 B) block transfers and for the directed case performs O((V + E B) · log2 V) block transfers. The running time of both algo-B rithms is O((V + E) · log V). For both priority queues with Decrease-Key operation, and for shortest path problems on general graphs, our results appear to give the first non-trivial cache-oblivious bounds